The candidate is a fellowship-trained neurologist dedicated to a career in the evaluation of health services for patients with Parkinson's Disease (PD) and other neuro-degenerative diseases. This application proposes a comprehensive program designed to allow the candidate to become an independent investigator in this area. The University of Pennsylvania has outstanding clinical and academic resources to support this proposal. The training component entails formal graduate education in clinical epidemiology and medical economics, specifically focusing on health services research. This training will satisfy the degree requirements for a Master of Science in Clinical Epidemiology (MSCE). The research component is an evaluation of the validity, reliability and responsiveness of preference-based outcomes in PD. These outcomes are a type of health related quality-of-life measure in which the desirability of a given health state is explicitly valued relative to alternative health states. The main use of preference-based outcomes is in cost-effectiveness analysis (CEA). In practice, societal preferences, which are the recommended metric for CEA, are difficult to measure. As a result, pre-scored multi-attribute health classification systems have been developed to approximate these preferences. The central hypothesis of the research component is that these pre-scored systems may not reflect societal preferences for health states encountered in PD. The specific aims of this study are: 1) To produce a series of vignettes describing PD-related health states, and to elicit societal preference weights for these vignettes; 2) To conduct a cross sectional study comparing this set of preferences to values derived from pre-scored multi- attribute health classification systems, and to preferences elicited from patients and caregivers; and 3) To conduct a longitudinal study to measure the reliability and responsiveness of preference-based measures in PD patients and their caregivers. The results from this study will have a direct application to all future CEA for PD-related interventions. In addition, the insights gained may be applied to other neuro-degenerative diseases including Alzheimer's Disease and Amyotrophic Lateral Sclerosis.